Quantifying Thematic Saturation in Qualitative Data Analysis

Bibliographic Data

ID2407552
AuthorsAndrew Lowe (0000-0002-3307-1150, Auckland University of Technology, corresponding author), Anthony C Norris (Auckland University of Technology), A Jane Farris (Auckland University of Technology), A Farris (Auckland University of Technology), Duncan R Babbage (0000-0002-9259-9246, Auckland University of Technology)
Year2018
Volume30
Issue3
Pages191-207
Publication date2018-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCAM (JOURNAL)
Journal identifiersISSN: 1087-8513 • E-ISSN: 1552-3969
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/1525822x17749386
OpenAlexW2793149982
LanguageEN
Citations received65
References cited17

An important aspect of qualitative research is reaching saturation-loosely, a point at which observing more data will not lead to discovery of more information related to the research questions. However, there has been no validated means of objectively establishing saturation. This article proposes a novel quantitative approach to measuring thematic saturation based on a sound statistical model. The model is validated on two data sets from different qualitative research projects involving interviews, focus groups, and literature surveys. The proposed model provides consistent estimates of saturation across data sets, within branches of data sets, and over the course of a research project. The model can be used for both quantifying saturation and estimating the number of observations required to achieve a specified level of saturation

Data collection · Data mining · Data science · Qualitative research · Saturation (graph theory) · Sociology · Statistics · Computer Science · Mathematics · Qualitative Comparative Analysis Research · Qualitative Research Methods and Applications · Qualitative Research Methods and Ethics